THE DETERMINANTS OF SHORT-TERM AND LONG-TERM PERFORMANCE OF INITIAL PUBLIC OFFERING: EVIDENCE FROM THE STOCK EXCHANGE OF THAILAND (SET) AND MARKET FOR ALTERNATIVE INVESTMENT (MAI)

Abstract

This study examines the determinants of short- and long-term IPO performance in the Stock Exchange of Thailand (SET) and the Market for Alternative Investment (mai) using IPO samples from 2014–2021. The research investigates how institutional market participants influence cumulative abnormal returns across various time horizons. Grounded in information asymmetry, certification, and signaling theories, the study applies multiple linear regression using OLS to analyze IPO performance. Findings show clear differences between the two markets. In the SET, underwriter reputation has no significant certification effect in either the short or long term. Institutional investor ownership has no short-term influence but shows a negative impact on three-year post-IPO cumulative abnormal returns. By contrast, Big-4 auditors have a consistently positive effect across all horizons. In the mai, underwriter reputation—measured by past IPO clients’ offering size—provides significant certification, reducing short-term information asymmetry. Institutional investor ownership is insignificant, while Big-4 auditors show no short-term effect but positively influence two-year cumulative abnormal returns. The results imply that the SET’s institutional environment diminishes the relevance of underwriter reputation while reinforcing Big-4 auditor signals. In the retail-driven mai, tangible certification through underwriter deal-scale reputation becomes more critical. This extended version enhances the previous paper by adding robustness checks using alternative measures of underwriter reputation. Only the past clients’ offering size–based measure shows a negatively significant impact on short-term cumulative abnormal returns. The study also identifies a systematic bias not detected previously when upgraded mai firms were included in long-term analysis. Additionally, it provides cross-environment insights comparing SET and mai.